really just subclassing list now

test/test_core.py

@@ -32,8 +32,6 @@ class AbstractNdarray_Check(object):
 
     def test_dict(self):
         d = self._inst._as_dict()
-        print("DONE")
-        print(d)
         other = type(self._inst)._from_dict(**d)
         self.demand_equal(other)
 
@@ -204,16 +202,24 @@ class Container_Test(Container_Check, unittest.TestCase):
         self._inst = tfields.Container([sphere, sphere2])
 
 
-class ContainerFolded_Test(Container_Check, unittest.TestCase):
+class ContainerNoList_Test(Container_Check, unittest.TestCase):
+    def demand_equal_tensors(self, one, other, atol=False, transformed=False):
+        if atol:
+            self.assertTrue(one.equal(other, atol=ATOL))
+        else:
+            self.assertTrue(one.equal(other))
+        if not transformed:
+            self.assertEqual(one.coord_sys, other.coord_sys)
+        self.assertEqual(one.name, other.name)
+
+    def demand_equal(self, other):
+        self.demand_equal_tensors(self._inst.items.items[0], other)
+        self.demand_equal_tensors(self._inst.items.items[1], other)
+
     def setUp(self):
-        sphere = tfields.Mesh3D.grid(
-            (1, 1, 1),
-            (-np.pi, np.pi, 3),
-            (-np.pi / 2, np.pi / 2, 3),
-            coord_sys='spherical')
-        sphere2 = sphere.copy() * 3
-        self._container = tfields.Container([sphere, sphere2])
-        self._inst = tfields.Container(self._container)
+        t = tfields.TensorFields([[1, 2, 3]])
+        self._inst = tfields.Container(t)
+        print(self._inst.items)
 
 
 if __name__ == '__main__':

tfields/core.py

@@ -469,7 +469,8 @@ class AbstractNdarray(np.ndarray):
             sub_dict = list_dict[key]
             list_dict[key] = []
             for index in sorted(list(sub_dict)):
-                bulk_type = sub_dict[index].get("bulk_type").tolist()
+                bulk_type = sub_dict[index].get("bulk_type")
+                # bulk_type = bulk_type.tolist() was necessary before. no clue
                 if isinstance(bulk_type, bytes):
                     # asthonishingly, this is not necessary under linux.
                     # Found under nt. ???
@@ -483,6 +484,8 @@ class AbstractNdarray(np.ndarray):
             '''
             bulk = kwargs.pop('bulk')
             bulk_type = kwargs.pop('bulk_type')
+            print("-"*100)
+            print(bulk, bulk_type, kwargs)
             obj = cls.__new__(cls, bulk, **kwargs)
 
             '''
@@ -1928,7 +1931,7 @@ class Container(AbstractNdarray):
     __slots__ = ["items", "labels"]
 
     def __new__(cls, items, **kwargs):
-        if issubclass(type(items), cls):
+        if issubclass(type(items), Container):
             kwargs.setdefault('labels', items.labels)
             items = items.items
         kwargs["items"] = items